When a Tritrophic Interaction Goes Wrong to the Third Level: Xanthoxylin From Trees Causes the Honeybee Larval Mortality in Colonies Affected by the River Disease

The “River Disease” (RD), a disorder impacting honeybee colonies located close to waterways with abundant riparian vegetation (including Sebastiania schottiana, Euphorbiaceae), kills newly hatched larvae. Forager bees from RD-affected colonies collect honeydew excretions from Epormenis cestri (Hemiptera: Flatidae), a planthopper feeding on trees of S. schottiana. First-instar honeybee larvae fed with this honeydew died. Thus, we postulated that the nectars of RD-affected colonies had a natural toxin coming from either E. cestri or S. schottiana. An untargeted metabolomics characterization of fresh nectars extracts from colonies with and without RD allowed to pinpoint xanthoxylin as one of the chemicals present in higher amounts in nectar from RD-affected colonies than in nectars from healthy colonies. Besides, xanthoxylin was also found in the aerial parts of S. schottiana and the honeydew excreted by E. cestri feeding on this tree. A larva feeding assay where xanthoxylin-enriched diets were offered to 1^st instar larvae showed that larvae died in the same proportion as larvae did when offered enriched diets with nectars from RD-colonies. These findings demonstrate that a xenobiotic can mimic the RD syndrome in honeybee larvae and provide evidence of an interspecific flow of xanthoxylin among three trophic levels. Further, our results give information that can be considered when implementing measures to control this honeybee disease.

     

The corrosion of mild steel in simulated SO2 containing atmospheres

Electrochemical tests were carried out on steel/steel multi-laminar cells under thin layers of sulphate solution simulating atmospheres with contents of 20, 50 and 75 μg m⁻³ of SO₂ and a relative humidity of 85%. Measurements of the current flowing between the two electrodes of the cell vs drying time and impedance measurements for different times were taken. Potentiodynamic cathodic polarization plots were also obtained for one concentration of contaminant at various drying times using three electrode multi-laminar cells. The results showed that the multi-laminar cells allowed the drying process of the thin electrolyte films to be followed. The use of electrochemical techniques gave information on the kinetics and mechanism of the corrosion process occurring during the drying period. Initially the process is controlled by oxygen diffusion through the liquid film, but for longer periods the control changes to the anodic reaction.     

A Python extension for the massively parallel multiphysics simulation framework waLBerla

We present a Python extension to the massively parallel HPC simulation toolkit waLBerla. waLBerla is a framework for stencil based algorithms operating on block-structured grids, with the main application field being fluid simulations in complex geometries using the lattice Boltzmann method. Careful performance engineering results in excellent node performance and good scalability to over 400,000 cores. To increase the usability and flexibility of the framework, a Python interface was developed. Python extensions are used at all stages of the simulation pipeline: they simplify and automate scenario setup, evaluation, and plotting. We show how our Python interface outperforms the existing text-file-based configuration mechanism, providing features like automatic nondimensionalization of physical quantities and handling of complex parameter dependencies. Furthermore, Python is used to process and evaluate results while the simulation is running, leading to smaller output files and the possibility to adjust parameters dependent on the current simulation state. C++ data structures are exported such that a seamless interfacing to other numerical Python libraries is possible. The expressive power of Python and the performance of C++ make development of efficient code with low time effort possible.     

Characterizing peers communities and dynamics in a P2P live streaming system

Despite the large number of works devoted to understand P2P live streaming applications, most of them put forth so far rely on characterizing the static view of these systems. In this work, we characterize the SopCast, one of the most important P2P live streaming applications. We focus on its dynamics behavior as well as on the community formation phenomena. Our results show that SopCast presents a low overlay topology diameter and low end-to-end shortest path. In fact, diameter is smaller than 6 hops in almost 90 % of the observation time. More than 96 % of peers’ end-to-end connections present only 3 hops. These values combined may lead to low latencies and a fast streaming diffusion. Second, we show that communities in SopCast are well defined by the streaming data exchange process. Moreover, the SopCast protocol does not group peers according to their Autonomous System. In fact, the probability that a community contains 50 % of its members belonging to the same AS (when we observe the largest AS of our experiments) is lower then 10 %. Peers exchange more data with partners belonging to the same community instead of peers inside the same AS. For the largest AS we have, less than 18 % of peer traffic has been exchanged with another AS partners. Finally, our analysis provides important information to support the future design of more efficient P2P live streaming systems and new protocols that exploit communities’ relationships.     

On absolute (robust) stability: slope restrictions andstability multipliers

Absolute stability for systems with several sector‐restricted and slope‐restricted nonlinearities is studied in this paper. A critical analysis of the multipliers is performed and the multipliers of Yakubovich type are chosen because the stability inequality is obtained with a minimum of technical assumptions. The main part of the paper is devoted to obtaining the Yakubovich‐type criterion in the unified context of stable, critical, and unstable cases for the linear part. The paper is motivated by the problem of pilot in‐the‐loop oscillations of the aircrafts where critical and unstable cases appear and the saturation nonlinearity is both sector and slope restricted. The paper contains some applications of the frequency domain inequalities. The conclusions show a ‘parsimony principle’: using as few free parameters as possible to obtain the largest possible domain of stability. The paper ends with conclusions and hints for further development. Copyright © 2011 John Wiley & Sons, Ltd.     

Mechanical resistance properties of gravel used in subsurface flow constructed wetlands: implications for clogging

Gravel constitutes the filter medium in subsurface flow constructed wetlands (SSF CWs) and its porosity and hydraulic conductivity decrease over time (clogging), limiting the lifespan of the systems. Using gravel of poor quality accelerates clogging in wetlands. In this study, gravel samples from six different wetland systems were compared with regards to their mineral composition and mechanical resistance properties. Results showed that both mineralogy and texture are related to mechanical resistance. Accordingly, gravel with high content of quartz (> 80%) showed a lower percentage of broken particles (0.18-1.03%) than those with lower content of quartz (2.42-4.56% media broken). Although granite is formed by high durability minerals, its non-uniform texture results in a lower resistance to abrasion (ca. 10% less resistance than calcareous gravel). Therefore, it is recommended to use gravels composed mainly of quartz or, when it is not available, limestone gravels (rounded and uniform) are recommended instead. The resistance to abrasion (LAA test) seems to be a good indicator to determine the mechanical properties of gravels used in CWs. It is recommended to use gravels with LAA below 30% in order to avoid a rapid clogging due to gravel crumbling and subsequent mineral solids accumulation.     

Density Displays for Data Stream Monitoring

In many business applications, large data workloads such as sales figures or process performance measures need to be monitored in real‐time. The data analysts want to catch problems in flight to reveal the root cause of anomalies. Immediate actions need to be taken before the problems become too expensive or consume too many resources. In the meantime, analysts need to have the “big picture” of what the information is about. In this paper, we derive and analyze two real‐time visualization techniques for managing density displays: (1) circular overlay d isplays which visualize large volumes of data without data shift movements after the display is full, thus freeing the analyst from adjusting the mental picture of the data after each data shift; and (2) variable resolution density displays which allow users to get the entire view without cluttering. We evaluate these techniques with respect to a number of evaluation measures, such as constancy of the display and usage of display space, and compare them to conventional d isplays with periodic shifts. Our real time data monitoring system also provides advanced interactions such as a local root cause analysis for further exploration. The applications using a number of real‐world data sets show the wide applicability and usefulness of our ideas.     

Exploiting User Interests to Characterize Navigational Patterns in Web Browsing Assistance

In order to be capable of exploiting context for pro-active information recommendation, agents need to extract and understand user activities based on their knowledge of the user interests. In this paper, we propose a novel approach for context-aware recommendation in browsing assistants based on the integration of user profiles, navigational patterns and contextual elements. In this approach, user profiles built using an unsupervised Web page clustering algorithm are used to characterize user ongoing activities and behavior patterns. Experimental evidence show that using longer-term interests to explain active browsing goals user assistance is effectively enhanced.

Multimodal focus attention and stress detection and feedback in an augmented driver simulator

This paper presents a driver simulator, which takes into account the information about the user’s state of mind (level of attention, fatigue state, stress state). The user’s state of mind analysis is based on video data and biological signals. Facial movements such as eyes blinking, yawning, head rotations, etc., are detected on video data: they are used in order to evaluate the fatigue and the attention level of the driver. The user’s electrocardiogram and galvanic skin response are recorded and analyzed in order to evaluate the stress level of the driver. A driver simulator software is modified so that the system is able to appropriately react to these critical situations of fatigue and stress: some audio and visual messages are sent to the driver, wheel vibrations are generated and the driver is supposed to react to the alert messages. A multi-threaded system is proposed to support multi-messages sent by the different modalities. Strategies for data fusion and fission are also provided. Some of these components are integrated within the first prototype of OpenInterface: the multimodal similar platform.